Dynamics and vibration analysis of suspended microchannel resonators based on strain gradient theory

Microsystem Technologies - In this paper, dynamics of a suspended microchannel resonator (SMR) will be derived using the strain gradient theory. Accordingly, the size dependent governing equation...     

Stability of nonlinear hybrid dynamical systems with time delay via sum of squares decomposition

Considering an infinite number of eigenvalues for time delay systems, it is difficult to determine their stability. We have developed a new approach for the stability test of time delay nonlinear hybrid systems. Construction of Lyapunov functions for hybrid systems is generally a difficult task, but once these functions are found, stability’s analysis of the system is straight-forward. In this paper both delay-independent and delay-dependent stability tests are proposed, based on the construction of appropriate Lyapunov-Krasovskii functionals. The methodology is based on the sum of squares decomposition of multivariate polynomials and the algorithmic construction is achieved through the use of semidefinite programming. The reduction techniques provide numerical solution of large-scale instances; otherwise they will be computationally infeasible to solve. The introduced method can be used for hybrid systems with linear or nonlinear vector fields. Finally simulation results show the correctness and validity of the designed method. Recommended by Editorial Board member Young Soo Suh under the direction of Editor Jae Weon Choi. The authors wish to express their thanks to Dr. A. Papachristodoulou and Dr. M. Peet for their helpful comments and suggestions. Mohammad Ali Badamchizadeh was born in Tabriz, Iran, in December 1975. He received the B.S. degree in Electrical Engineering from University of Tabriz in 1998 and the M.Sc. degree in Control Engineering from University of Tabriz in 2001. He received the Ph.D. degree in Control Engineering from University of Tabriz in 2007. He is now an Assistant Professor in the Faculty of Electrical and Computer Engineering at University of Tabriz. His research interests include Hybrid dynamical systems, Stability of systems, Time delay systems, Robot path planning. Sohrab Khanmohammadi received the B.S. degree in Industrial Engineering from Sharif University, Iran in 1977 and the M.Sc. degree in Automatic from University Paul Sabatie, France in 1980 and the Ph.D. degree in Automatic from National University, ENSAE, France in 1983. He is now a Professor of Electrical Engineering at University of Tabriz. His research interests are Fuzzy control, Artificial Intelligence applications in control and simulation on industrial systems and human behavior. Gasem Alizadeh was born in Tabriz, Iran in 1967. He received the B.S. degree in Electrical Engineering from Sharif University, Iran in 1990 and the M.Sc. degree from Khajeh Nasir Toosi University, Iran in 1993 and the Ph.D. degree in Electrical Engineering from Tarbiat Modarres University, Iran in 1998. From 1998, he is a Member of University of Tabriz in Iran. His research interests are robust and optimal control, guidance, navigation and adaptive control. Ali Aghagolzadeh was born in Babol, Iran. He received the B.S. degree in Electrical Engineering in 1985 from University of Tabriz, Tabriz, Iran, and the M.Sc. degree in Electrical Engineering in 1988 from the Illinois Institute of Technology, Chicago, IL. He also attended the School of Electrical Engineering at Purdue University in August 1998 where he was also employed as a part-time research assistant and received the Ph.D. degree in 1991. He is currently an Associate Professor of Electrical Engineering at University of Tabriz, Tabriz, Iran. His research interests include digital signal and image processing, image coding and communication, computer vision, and image analysis.     

Connectivity preserving localized coverage algorithm for area monitoring using wireless sensor networks

Efficient network coverage and connectivity are the requisites for most Wireless Sensor Network (WSN) deployments, particularly those concerned with area monitoring. Due to the resource constraints of the sensor nodes, redundancy of coverage area must be reduced for effective utilization of the available resources. If two nodes have the same coverage area in their active state, and if both the nodes are activated simultaneously, it leads to redundancy in network and wastage of precious sensor resources. In this paper, we address the problem of network coverage and connectivity and propose an efficient solution to maintain coverage, while preserving the connectivity of the network. The proposed solution aims to cover the area of interest (AOI), while minimizing the count of the active sensor nodes. The overlap region of two sensor nodes varies with the distance between the nodes. If the distance between two sensor nodes is maximized, the overall coverage area of these nodes will also be maximized. Also, to preserve the connectivity of the network, each sensor node must be in the communication range of at least one other node. Results of simulation of the proposed solution indicate up to 95% coverage of the area, while consuming very less energy of 9.44 J per unit time in the network, simulated in an area of 2500 m².     

PGSW-OS: a novel approach for resource management in a semantic web operating system based on a P2P grid architecture

A web operating system is an operating system that users can access from any hardware at any location. A peer-to-peer (P2P) grid uses P2P communication for resource management and communication between nodes in a grid and manages resources locally in each cluster, and this provides a proper architecture for a web operating system. Use of semantic technology in web operating systems is an emerging field that improves the management and discovery of resources and services. In this paper, we propose PGSW-OS (P2P grid semantic Web OS), a model based on a P2P grid architecture and semantic technology to improve resource management in a web operating system through resource discovery with the aid of semantic features. Our approach integrates distributed hash tables (DHTs) and semantic overlay networks to enable semantic-based resource management by advertising resources in the DHT based upon their annotations to enable semantic-based resource matchmaking. Our model includes ontologies and virtual organizations. Our technique decreases the computational complexity of searching in a web operating system environment. We perform a simulation study using the Gridsim simulator, and our experiments show that our model provides enhanced utilization of resources, better search expressiveness, scalability, and precision.     

Alternating active-phase algorithm for multimaterial topology optimization problems: a 115-line MATLAB implementation

Structural and Multidisciplinary Optimization - A new algorithm for the solution of multimaterial topology optimization problems is introduced in the present study. The presented method is based on...     

Human eye sclera detection and tracking using a modified time-adaptive self-organizing map

This paper investigates the use of time-adaptive self-organizing map (TASOM)-based active contour models (ACMs) for detecting the boundaries of the human eye sclera and tracking its movements in a sequence of images. The task begins with extracting the head boundary based on a skin-color model. Then the eye strip is located with an acceptable accuracy using a morphological method. Eye features such as the iris center or eye corners are detected through the iris edge information. TASOM-based ACM is used to extract the inner boundary of the eye. Finally, by tracking the changes in the neighborhood characteristics of the eye-boundary estimating neurons, the eyes are tracked effectively. The original TASOM algorithm is found to have some weaknesses in this application. These include formation of undesired twists in the neuron chain and holes in the boundary, lengthy chain of neurons, and low speed of the algorithm. These weaknesses are overcome by introducing a new method for finding the winning neuron, a new definition for unused neurons, and a new method of feature selection and application to the network. Experimental results show a very good performance for the proposed method in general and a better performance than that of the gradient vector field (GVF) snake-based method.     

The utilization of soft transformation and genetic algorithm to model two sources of uncertainty of Indicator Kriging

Indicator Kriging (IK) is a geostatistical method that uses observation points to quantify the probabilities at which a set of thresholds are exceeded at unmeasured points. To improve IK accuracy, the interpolation process should consider its uncertainty sources. By doing this, we also maintain its ability to provide the conditional cumulative distribution function (ccdf), which is a reliable measure of local uncertainty. This study modeled two IK uncertainty sources, i.e., measurement errors attached to observation points and subjective threshold choices. Soft Indicator Kriging (SIK), which uses a soft transformation for observation points, considers the measurement errors of these two sources. To select the thresholds objectively, a genetic algorithm (GA) was performed to obtain the optimum set of thresholds related to an objective function, which minimized the mean absolute error (MAE).     

Design and performance evaluation of a fuzzy based traffic conditioner for differentiated services

The current Internet can only provide the best-effort services. By growing the Internet and its applications, new services with different requirements are developed. The differentiated services (Diffserv) [S. Blake, M. Carlson, E. Davies, Z. Wang, W. Weiss, An Architecture for Differentiated Services, IETF RFC 2475, 1998; K. Nichols, V. Jacobson, L. Zhang, A Two-bit Differentiated Services Architecture for the Internet, IETF RFC 2638, July 1999; T. Li, Y. Rekhter, A Provider Architecture for Differentiated Services and Traffic Engineering (PASTE), IETF RFC 2430, October 1998] is a scalable model for providing end-to-end quality of services. A Diffserv router consists of different components including classifier, meter, marker, dropper, shaper and scheduler. In this paper, we use the benefits of the fuzzy logic controller to design a fuzzy based traffic conditioner for Internet differentiated services. Our proposed model consists of three major parts: a fuzzy meter/marker (FM), a fuzzy active queue management (FAQM) algorithm and a fuzzy scheduler (FS). The proposed FM used to measure and mark the input traffic is based on the single rate three colors meter (srTCM) mechanism [J. Heinane, et al., A Single Rate Three Color Marker, RFC 2697, September 1999]. The FM meters an IP packet stream and marks its packets GREEN, YELLOW, or RED. The proposed FAQM is a fuzzy implementation of the well-known BLUE active queue management (AQM) algorithm [W. Feng, D. Kandlur, D. Saha, K. Shin, BLUE: A New Class of Active Queue Management Algorithms U. Michigan CSE-TR-387-99, April 1999]. To achieve a good throughput and reasonable packet loss ratio, the proposed FAQM mechanism employs a fuzzy logic controller. The third part of the proposed fuzzy traffic conditioner is FS. It is based on the traditional weighted fair queue (WFQ) mechanism [A. Demers, S. Keshav, S. Shenker, Analysis and simulation of a fair queueing algorithm, in: SIGCOMM Symposium on Communications Architectures and Protocols, Austin, Texas, September 1989, pp. 1–12] that tunes the weight of each queue by a fuzzy logic controller. To evaluate the performance of the proposed model, we developed a software in C++ environment to simulate it. Different network topologies with different traffic parameters were performed. The simulation results easily helped us to judge the merit of the proposed FM, FAQM and FS because of their remarkable performance over the traditional non-fuzzy mechanisms.     

Adaptive sliding mode control of n$n$ flexible-joint robot manipulators in the presence of structured and unstructured uncertainties

Multibody System Dynamics - This study investigates a voltage-based adaptive sliding mode control (VB-ASMC) to tracking the position of an $n$ rigid-link flexible-joint (RLFJ) robot manipulator...     

Improving performance of node clustering in wireless sensor networks using meta-heuristic algorithms and a novel validity index

The use of wireless sensor networks has significantly increased in the last decade. These networks consist of a large number of small sensors, which are efficient tools for data collection from different environments. The data collected by these sensors will be usually transmitted to a base station that will provide the end user’s data. In order to improve scalability of such networks, sensor nodes can be grouped into non-overlapped clusters. These clusters create a hierarchical design in wireless sensor networks that leads to better energy utilization and thus increase the network’s lifetime. Using validity indexes and meta-heuristic algorithms are common ways to improve performance of clustering. In this paper, we provide a new validity index called ASCS by enhancing the Chou and Su (CS) validity index, and improve the performance of the meta-heuristic algorithms for clustering using this new validity index as their objective functions. Differential evolution and harmony search are two algorithms that will be used for this purpose. The experimental results show the better performance of ASCS index comparing to Davies and Bouldin (DB) and CS validity indexes in determining appropriate number of clusters and determining proper clusters’ members.